Dynamic coupling between heart rate and ventricular repolarisation

Sex and Rate Change Differences in QT/RR Hysteresis in Healthy Subjects

While it is now well-understood that the extent of QT interval changes due to underlying heart rate differences (i.e., the QT/RR adaptation) needs to be distinguished from the speed with which the QT interval reacts to heart rate changes (i.e., the so-called QT/RR hysteresis), gaps still exist in the physiologic understanding of QT/RR hysteresis processes. This study was designed to address the questions of whether the speed of QT adaptation to heart rate changes is driven by time or by number of cardiac cycles; whether QT interval adaptation speed is the same when heart rate accelerates and decelerates; and whether the characteristics of QT/RR hysteresis are related to age and sex. The study evaluated 897,570 measurements of QT intervals together with their 5-min histories of preceding RR intervals, all recorded in 751 healthy volunteers (336 females) aged 34.3 ± 9.5 years. Three different QT/RR adaptation models were combined with exponential decay models that distinguished time-based and interval-based QT/RR hysteresis. In each subject and for each modelling combination, a best-fit combination of modelling parameters was obtained by seeking minimal regression residuals. The results showed that the response of QT/RR hysteresis appears to be driven by absolute time rather than by the number of cardiac cycles. The speed of QT/RR hysteresis was found decreasing with increasing age whilst the duration of individually rate corrected QTc interval was found increasing with increasing age. Contrary to the longer QTc intervals, QT/RR hysteresis speed was faster in females. QT/RR hysteresis differences between heart rate acceleration and deceleration were not found to be physiologically systematic (i.e., they differed among different healthy subjects), but on average, QT/RR hysteresis speed was found slower after heart rate acceleration than after rate deceleration.

Categorization and theoretical comparison of quantitative methods for assessing QT/RR hysteresis

BACKGROUND

In the human electrocardiogram, there is a lag of adaptation of the QT interval to heart rate changes, usually termed QT/RR hysteresis (QT-hys). Subject-specific quantifiers of QT-hys have been proposed as potential biomarkers, but there is no consensus on the choice of the quantifier.

METHODS

A comprehensive literature search was conducted to identify original articles reporting quantifiers of repolarization hysteresis from the surface ECG in humans.

RESULTS

Sixty articles fulfilled our inclusion criteria. Reported biomarkers were grouped under four categories. A simple mathematical model of QT/RR loop was used to illustrate differences between the methods. Category I quantifiers use direct measurement of QT time course of adaptation. They are limited to conditions where RR intervals are under strict control. Category IIa and IIb quantifiers compare QT responses during consecutive heart rate acceleration and deceleration. They are relevant when a QT/RR loop is observed, typically during exercise and recovery, but are not robust to protocol variations. Category III quantifiers evaluate the optimum RR memory in dynamic QT/RR relationship modeling. They estimate an intrinsic memory parameter independent from the nature of RR changes, but their reliability remains to be confirmed when multiple memory parameters are estimated. Promising approaches include the differentiation of short-term and long-term memory and adaptive estimation of memory parameters.

CONCLUSION

Model-based approaches to QT-hys assessment appear to be the most versatile, as they allow separate quantification of QT/RR dependency and QT-hys, and can be applied to a wide range of experimental settings.

Wiener-Granger causality in QT-HP variability interactions

The study exploits a Wiener-Granger causality (WGC) approach in the time domain to assess directionality of the dynamical interactions between QT interval and heart period (HP) during a graded head-up tilt protocol challenging the cardiovascular control as a function of the tilt table inclination. QT interval and HP are approximated from the surface ECG as the temporal distance between the R-wave apex and T-wave offset and between two consecutive R-wave peaks respectively. The adopted WGC approach accounts for the confounding effect of respiration (RESP) affecting both QT and HP. Causality ratios (CRs) from HP to QT given RESP (CRHP→QT|RESP) and from QT to HP given RESP (CRQT→HP|RESP) were computed and their significance was tested via F-test. We found that, regardless of the tilt table angle, CRHP→QT|RESP is significant, while CRQT→HP|RESP is negligible. CRHP→QT|RESP showed a trend towards a decrease with tilt table angle. These findings suggested that the causal direction from HP over QT is dominant compared to the reverse one and sympathetic activation induced a QT-HP uncoupling.

Measure of the QT-RR dynamic coupling in patients with the long QT syndrome

BACKGROUND

The patients with the long QT syndrome type-1 (LQT-1) have an impaired adaptation of the QT interval to heart rate changes. Yet, the description of the dynamic QT-RR coupling in genotyped LQT-1 has never been thoroughly investigated.

METHOD

We propose a method to model the dynamic QT-RR coupling by defining a transfer function characterizing the relationship between a QT interval and its previous RR intervals measured from ambulatory Holter recordings. Three parameters are used to characterize the QT-RR coupling: a fast gain (Gain(F) ), a slow gain (Gain(L) ), and a time constant (τ). We investigated the values of these parameters across genders, and in genotyped LQT-1 patients with normal QTc interval duration (QTc < 470 ms).

RESULTS

The QT-RR dynamic profiles are significantly different between LQT-1 patients (97) and controls (154): LQT-1 have longer QTc interval (453 ± 35 vs. 384 ± 26 ms, P < 0.0001), and an increased dependency of the QT interval to previous RR changes revealed by a larger Gain(L) (0.22 ± 0.06 vs. 0.18 ± 0.07, P < 0.0001) and Gain(F) (0.05 ± 0.02 vs. 0.03 ± 0.01, P < 0.0001). Importantly, LQT-1 patients have a faster QT dynamic response to previous RR changes described by τ: 122 ± 44 vs. 172 ± 92 beats (P < 0.0001). This faster QT dynamic response of the QT-RR dynamic coupling remained in LQT-1 patients with QTc in a normal range (<430 ms).

CONCLUSIONS

The measurement of QT-RR dynamic coupling could be used in patients suspected to carry a concealed form of the LQT-1 syndrome, or to provide insights into the types of arrhythmogenic triggers a patient may be prone to.

Frequency domain assessment of the coupling strength between ventricular repolarization duration and heart period during graded head-up tilt

We test the hypothesis that the degree of correlation between ventricular repolarization duration (VRD) and heart period (HP) carries information on cardiac autonomic regulation. The degree of correlation was assessed in the frequency domain using squared coherence function during an experimental protocol known to gradually induce a shift of sympathovagal balance toward sympathetic predominance (ie, graded head-up tilt). We observed a progressive decrease of squared coherence with tilt table inclination, thus confirming the working hypothesis. The VRD-HP uncoupling occurs in the high-frequency band, centered on the respiratory rate, thus suggesting that vagal withdrawal is responsible for the VRD-HP uncoupling.

Highly automated QT measurement techniques in 7 thorough QT studies implemented under ICH E14 guidelines

Thorough QT (TQT) studies are designed to evaluate potential effect of a novel drug on the ventricular repolarization process of the heart using QTc prolongation as a surrogate marker for torsades de pointes. The current process to measure the QT intervals from the thousands of electrocardiograms is lengthy and expensive. In this study, we propose a validation of a highly automatic-QT interval measurement (HA-QT) method. We applied a HA-QT method to the data from 7 TQT studies. We investigated both the placebo and baseline-adjusted QTc interval prolongation induced by moxifloxacin (positive control drug) at the time of expected peak concentration. The comparative analysis evaluated the time course of moxifloxacin-induced QTc prolongation in one study as well. The absolute HA-QT data were longer than the FDA-approved QTc data. This trend was not different between ECGs from the moxifloxacin and placebo arms: 9.6 ± 24 ms on drug and 9.8 ± 25 ms on placebo. The difference between methods vanished when comparing the placebo-baseline-adjusted QTc prolongation (1.4 ± 2.8 ms, P = 0.4). The differences in precision between the HA-QT and the FDA-approved measurements were not statistically different from zero: 0.1 ± 0.1 ms (P = 0.7). Also, the time course of the moxifloxacin-induced QTc prolongation adjusted for placebo was not statistically different between measurements methods.

Excitation specificity of repolarization parameters

The excitation specificity of QT dynamic parameters was tested on three groups of subjects: healthy subjects; non-medicated hypertensive subjects with metabolic syndrome; and subjects with essential hypertension. Four different excitations of RR were used: bicycling exercise; tilt with breathing 0.1 and 0.33 Hz; and deep breathing. Linear dynamic feedback model of QT/RR coupling was supposed at the analysis and next repolarization parameters were tested: QTc; gain of QT/RR coupling for slow and fast RR variability; time constant of QT adaptation; and random QT variability.

RESULTS

Dynamic repolarization parameters statistically significantly depend on the type of RR excitation. The gain of QT/RR coupling for slow RR variability, the time constant of QT adaptation and QTc are maximal at RR excitation given by the bicycling exercise. The frequency of breathing, i.e. corresponding vagal modulation has no effect on repolarization parameters. The measurements with deep breathing, without any other slow excitation of heart rate, has low signal-to-noise ratio of analyzed data and resulting QT parameters are inaccurate.

CONCLUSION

The use of heart rate excitation and all measurements conditions should be defined for the exact analysis of the repolarization dynamic parameters.

Use of a novel transfer function to reduce repolarization interval hysteresis

BACKGROUND

Cardiac repolarization is assessed by the QT interval on the surface electrocardiogram and varies with the heart rate. Standard QT corrections (QTc) do not account for the lag in QT change following a change in heart rate (QT hysteresis). Our group has developed and tested a transfer function (TRF) model to assess the effectiveness of a dynamic model of QT/RR coupling in eliminating hysteresis.

METHODS

We studied three groups: group I, healthy volunteers (n = 23, 41 ± 17 years); group II, hypertensive patients (n = 25, 45 ± 11 years); and group III, patients in a predominately paced rhythm (n = 5, 75 ± 6 years). To vary the heart rate, either exercise bicycling in the supine position (groups I and II) or manipulation of the pacemaker parameters (group III) was done. We then compared a dynamic TRF model with a model based on weighted averages of previous RR intervals. Two parameters were tested: root mean square (RMS) of the error signal between measured and computed QT and the elimination of hysteretic loops.

RESULTS

TRF-based measurements eliminated hysteresis in 22/23 (95%) group I patients, 21/25 (84%) group II patients, and 4/5 (80%) group III patients. When hysteresis elimination was not complete, the QT drift that followed RR intervals was different before and after bicycling (100 ms). In these patients, the corresponding QT interval did not significantly change during this period. The TRF model was found superior to the other tested models with respect to both analyzed parameters (RMS and hysteresis elimination).

CONCLUSION

The TRF model limited QT hysteresis in healthy, hypertensive, and pacemaker-dependent patients. In addition, an important finding of QT drift in patients with hypertension was identified. With further study in these and other diseased states, the TRF model may improve our ability to measure accurately cardiac repolarization and to determine arrhythmia risk.

Dynamic QT/RR coupling in patients with pacemakers

The dynamic coupling between heart rate intervals (RR) and ventricular repolarization (QT) is analyzed. The analysis is based on measurements of 11 patients with pacemaker. In each measurement, there are at least 4 abrupt changes of RR preset by the pacemaker. With such a protocol, RR changes are important and well defined while disturbing factors and noise sources (such as those related with motion of patient) are minimized. The QT/RR coupling was described by 3 parameters (a1, b2, b3) transfer function (TRF) selected on the basis of a statistical analysis of performances of different TRF models. We found that our model is by far the best in its class: with more parameters (higher order models) the residuals remain almost the same while the extra parameters display variability much larger than that of our parameters. For all measurements, our TRF model describes more than 70% of QT variability. Within the patient set, we found interesting differences concerning dynamic non-linearity (response times longer with decreasing RR intervals than with increasing RR).